Extract slices from compressed volumetric data
Project description
quickslice
A simple python package to compress large volumetric data and dynamically extract slices from the compressed volume.
Usage
Build
quickslice build path/to/directory
quickslice build path/to/directory --size 256 256 256
Slice
quickslice slice file.cct -z 0
quickslice slice file.cct -z 0.5
quickslice slice file.cct -x 0.7
quickslice slice file.cct -y 1
Files
quickslice
quickslice is the main binary file
build.py
build.py takes input of a directory containing slices in alphanumeric order and converts it to a CCT (Compressed Computed Tomography) file of size 128 x 128 x 128
slice.py
slice.py is used to extract a slice from a cct file. The following command shows the xy plane at z = 0 of file.cct
Additional Stuff
The z=0 plane output
More examples
More examples and commands with options can be found in examples
CCT File format
Compressed Computed Tomography Files
CCT files represent GBs of Tomographic Datasets in a single compressed file. The file size depends on the output size. The default size is 128 x 128 x 128 and the size of the output file is between 7 MB to 12 MB
Note: Refrain from using CCT files for in-detail visualisation. CCT files are built using a super-lossy conversion technique and are meant to be used for a small quick preview of planes extracted from 3d volumes.
Representation:
Line 1: sizeX,sizeY,sizeZ
Line 2 to Line (sizeZ + 1): Z-Slice representation
The following voxels:
[
[
[0,0,1],
[0,0,1],
[0,1,1],
[0,1,1],
[1,1,1]
],
[
[0,0,1],
[0,0,1],
[0,1,1],
[0,1,1],
[1,1,1]
],
[
[0,0,1],
[0,0,1],
[0,1,1],
[0,1,1],
[1,1,1]
],
[
[0,0,1],
[0,0,1],
[0,1,1],
[0,1,1],
[1,1,1]
]
]
will be represented as
3,5,4
0,0,1,0,0,1,0,1,1,0,1,1,1,1,1
0,0,1,0,0,1,0,1,1,0,1,1,1,1,1
0,0,1,0,0,1,0,1,1,0,1,1,1,1,1
0,0,1,0,0,1,0,1,1,0,1,1,1,1,1
Example
file.cct is a 128 x 128 x 128 grayscale tomographic model
Project details
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